Journal
PROCEEDINGS OF THE 2023 ACM INTERNATIONAL CONFERENCE ON MULTIMEDIA RETRIEVAL, ICMR 2023
Volume -, Issue -, Pages 597-601Publisher
ASSOC COMPUTING MACHINERY
DOI: 10.1145/3591106.3592281
Keywords
video retrieval; evaluation; benchmarking; quality assurance
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This paper proposes a process for refining known-item and open-set type queries in interactive video retrieval evaluations. It emphasizes the importance of proper task interpretations.
Different task interpretations are a highly undesired element in interactive video retrieval evaluations. When a participating team focuses partially on a wrong goal, the evaluation results might become partially misleading. In this paper, we propose a process for refining known-item and open-set type queries, and preparing the assessors that judge the correctness of submissions to openset queries. Our findings from recent years reveal that a proper methodology can lead to objective query quality improvements and subjective participant satisfaction with query clarity.
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